Observational studyTranslational vision science & technology2025
Novel Subclassification of Presbyopia Based on Lens Functional and Structural Features.
Observational study in Translational vision science & technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: The purpose of this study was to classify eyes with presbyopia using lens functional and structural features to aid in surgical decision making. Methods: This cross-sectional observational study included healthy volunteers or those solely affected by presbyopia. Lens function was assessed using dysfunction lens index (DLI), whereas lens density was evaluated with Pentacam (LD-P) and swept-source optical coherence tomography (LD-S). Principal component analysis (PCA) and k-means clustering classified participants into non-lens surgery (NLS) and lens surgery (LS) groups. A scoring system was developed from the optimal cutoff values for simplified diagnosis, with a website created for automatic classification. Results: Totally, 352 eyes of 176 patients were studied, with a mean age of 46.1 ± 6.2 years and a mean axial length of 24.42 ± 1.62 mm. Among them, 268 (76.1%) eyes were diagnosed with presbyopia. The top 5.2% (14/268) of presbyopia cases with the highest variability were excluded by PCA. Subsequently, 138 eyes (51.5%) were clustered into the NLS group, and 116 eyes (43.3%) into the LS group. The LS group presented lower DLI and higher lens density compared to the NLS group (all P < 0.001). Optimal cutoff values were determined as follows: DLI = 7.75, LD-P = 8.75, and LD-S = 60.05 pixel units. The scoring system demonstrated that combining DLI with LD-P achieved the highest diagnostic efficacy. A website (www.zhu-zhou-lf.com) was developed for automatic classification. Conclusions: We proposed a novel classification of presbyopia using lens functional and structural features. Translational Relevance: This classification, integrating DLI and lens density values, offers a diagnostic tool to guide surgical decisions in presbyopia.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.